Accepted for/Published in: JMIR Research Protocols
Date Submitted: Jun 20, 2020
Date Accepted: Oct 13, 2020
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Artificial Intelligence-powered smart phone application to facilitate medication adherence: Protocol for Human Factors Based Design
ABSTRACT
Background:
Medication guides consisting of crucial interactions and side effects are extensive and complex. Due to the exhaustive information, patients do not retain the necessary medication information which can result in hospitalizations and medication nonadherence. A gap exists in understanding patients’ cognition of managing complex medication information. However, advancements in technology and artificial intelligence (AI) allow us to understand patient cognitive processes to design an application to better provide important medication information to patients.
Objective:
To improve the design of an innovative AI and human-factors based interface that supports patients’ medication information comprehension that could potentially improve medication adherence.
Methods:
Aim 1: Aim 1 has 3 phases: 1) an observational study to understand patient perception of fear and biases regarding medication information, 2) eye-tracking study to understand attention locus for medication information, and 3) Psychological Refractory Period (PRP) Paradigm study to understand functionalities. Observational data will be collected such as audio and video recordings, gaze mapping, and time from PRP. 50 patients of ages 18-65 years who started at least one new medication for which we developed a visualization information and cognitive status of 34 will be included in this aim of the study. Aim 2: To iteratively design and evaluate an AI powered medication information visualization interface as a smart phone application with the knowledge gained from each component of aim 1. The interface will be assessed through two usability surveys. For the survey, 300 patients ages 18-65 years with diabetes, cardiovascular diseases or mental health disorder will be recruited for this portion. Data from the surveys will be analyzed through exploratory factor analysis. Aim 3: In order to test the prototype, there will be a 2-arm study design. This aim will include 900 patients ages 18-65 with Internet access, without any cognitive impairment, and with at least two medications. Patients will be sequentially randomized. Three surveys will be used to assess the primary outcome of medication information comprehension and secondary outcome of medication adherence at 12 weeks.
Results:
Preliminary data collection is underway in the year 2020-2021.
Conclusions:
This study will lead the future of artificial intelligence-based innovative digital interface design and act as the aid to improving medication comprehension, which may improve medication adherence. The results from this study will also open up future research opportunities in understanding how patients manage complex medication information and inform the format and design for innovative AI powered digital interfaces for medication guide.
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